Machine recognition of input to derive therefrom a recognized output is a useful and common process. Such recognition includes taking a visible input of textual characters and optically recognizing the visible characters as text, sometimes called optical character recognition, or OCR. Also, machine recognition can take the form of taking an audible input such as the spoken voice of a user and automatically determining the words and phrases spoken by the user, a process sometimes referred to as automatic speech recognition, or ASR.
Optical character recognition (OCR) systems are known and used for machine recognition of printed characters and text. Generally, an OCR system is equipped with an optical sensor that may include a camera or scanner apparatus to optically detect the printed text on a page. Also, the OCR system is adapted to take an output from its optical sensor or scanner element and feed that into a computerized recognition apparatus that determines the alphabetical or textual elements from the scanned images on the page. An output apparatus such as a printer or monitor screen provides a visual output to a user based on the results of the optical recognition process. The OCR system can also cause the scanned information and the output of the recognition step to be stored in a computer file such as a text editor file.
Automatic speech recognition (ASR) has developed into a field of art that combines knowledge of user speech patterns as well as algorithms for determining the words and phrases being spoken. ASR is sometimes related to a corresponding process for producing speech-like sounds from a machine, known as speech synthesis. Those skilled in the art may appreciate the underlying techniques of OCR, ASR and speech synthesis, and these will not be presented here in detail beyond that needed to understand the present disclosure and embodiments.
Systems and methods for machine recognition are generally prone to errors of various kinds. In the context of OCR, such errors can be the result of imperfect scanning or optical processing of a scene, e.g., printed words on a paper surface. The errors can also result from poor lighting or other conditions such as bad original printing quality or a poor or dirty or damaged print medium onto which the original text is printed. In addition, the algorithms used to recognize the scanned information can be flawed or incomplete and result in errors in the output of an OCR system. Similarly, acoustical systems for ASR and the algorithms for processing speech in a machine are imperfect and can return incorrect results. The errors from ASR systems are generally attributed to variations in speech by the speaker, imperfections in the acoustical detection or microphone or sound processing apparatus for ASR, and from flawed or resource-limited algorithms for performing the ASR process on detected sound data.
It is a known goal of machine recognition systems such as OCR and ASR systems to reduce the number or frequency or severity of the errors in these systems, yet these systems and methods remain imperfect despite recent improvements to these systems and methods. It is also a goal to provide useful automated machine search tools for searching information in a database or network and returning a result of the search to a user.